Scoring functions api fixed.

bin/lgd_generate_glowworm_positions.py

@@ -6,18 +6,12 @@
 import os
 from lightdock.pdbutil.PDBIO import create_pdb_from_points
 from lightdock.util.logger import LoggingManager
+from lightdock.util.parser import valid_file
 
 
 log = LoggingManager.get_logger("generate_glowworm_positions")
 
 
-def valid_file(file_name):
-    """Checks if it is a valid file"""
-    if not os.path.exists(file_name):
-        raise argparse.ArgumentTypeError("The file does not exist")
-    return file_name
-
-
 def parse_output_file(lightdock_output):
     glowworm_translations = []
 

bin/lgd_generate_trajectory.py

@@ -17,18 +17,12 @@
 from lightdock.pdbutil.PDBIO import parse_complex_from_file, write_pdb_to_file
 from lightdock.structure.complex import Complex
 from lightdock.prep.simulation import get_setup_from_file
+from lightdock.util.parser import valid_file
 
 
 log = LoggingManager.get_logger("lgd_generate_trajectory")
 
 
-def valid_file(file_name):
-    """Checks if it is a valid file"""
-    if not os.path.exists(file_name):
-        raise argparse.ArgumentTypeError("The file does not exist")
-    return file_name
-
-
 def parse_command_line():
     parser = argparse.ArgumentParser(prog="lgd_generate_trajectory")
     parser.add_argument(

bin/lgd_move_anm.py

@@ -10,6 +10,7 @@
 from lightdock.pdbutil.PDBIO import parse_complex_from_file, write_pdb_to_file
 from lightdock.structure.complex import Complex
 from lightdock.util.logger import LoggingManager
+from lightdock.util.parser import valid_file
 from lightdock.constants import DEFAULT_EXTENT_MU, DEFAULT_EXTENT_SIGMA
 
 log = LoggingManager.get_logger("lgd_move_anm")
@@ -18,13 +19,6 @@
 RANDOM_SEED = 324324
 
 
-def valid_file(file_name):
-    """Checks if it is a valid file"""
-    if not os.path.exists(file_name):
-        raise argparse.ArgumentTypeError("The file does not exist")
-    return file_name
-
-
 def parse_command_line():
     parser = argparse.ArgumentParser(prog="lgd_move_anm")
     parser.add_argument(

bin/lgd_rank.py

@@ -61,8 +61,8 @@ def parse_command_line():
         args = parse_command_line()
 
         solutions = []
-        contacts = []
-        rmsds = []
+        contacts = {}
+        rmsds = {}
         if os.path.isfile(EVALUATION_FILE):
             contacts, rmsds = read_rmsd_and_contacts_data(EVALUATION_FILE)
 

lightdock/constants.py

@@ -4,73 +4,73 @@
 DEFAULT_NUM_SWARMS = 400
 DEFAULT_NUM_GLOWWORMS = 200
 
-"""GSO algorithm constants"""
-# Maximum translation allowed at initialization (in Angstroms)
+# GSO algorithm constants
 MAX_TRANSLATION = 30
-# Quaternion default value for its components
+"""Maximum translation allowed at initialization (in Angstroms)"""
 MAX_ROTATION = 1.0
-# Default generic GSO step (does only apply to J* functions
+"""Quaternion default value for its components"""
 DEFAULT_STEP_SIZE = 0.03
-# Interpolation step for translation (in %)
+"""Default generic GSO step (does only apply to J* functions"""
 DEFAULT_TRANSLATION_STEP = 0.5
-# Normalized SLERP step. 1 means full jump, 0 means no movement
+"""Interpolation step for translation (in %)"""
 DEFAULT_ROTATION_STEP = 0.5
-# Seed for the random number generator in the GSO algorithm
+"""Normalized SLERP step. 1 means full jump, 0 means no movement"""
 GSO_SEED = 324324
-# Seed for the random number generator used for calculating starting points
+"""Seed for the random number generator in the GSO algorithm"""
 STARTING_POINTS_SEED = 324324
+"""Seed for the random number generator used for calculating starting points"""
 
-"""Normal modes"""
-# Default number of normal modes to consider for receptor
+# Normal modes
 DEFAULT_NMODES_REC = 10
-# Default number of normal modes to consider for ligand
+"""Default number of normal modes to consider for receptor"""
 DEFAULT_NMODES_LIG = 10
-# Default RMSD interval at which conformations will be sampled through ANM
+"""Default number of normal modes to consider for ligand"""
 DEFAULT_ANM_RMSD = 0.5
-# Default mean and std for the Normal distribution for random ANM extents
+"""Default RMSD interval at which conformations will be sampled through ANM"""
 DEFAULT_EXTENT_MU = 0.0
+"""Default mean for the Normal distribution for random ANM extents"""
 DEFAULT_EXTENT_SIGMA = 1.0
+"""Default std for the Normal distribution for random ANM extents"""
 # Boundaries, this does not affect to modes generation
 MIN_EXTENT = 0.0
 MAX_EXTENT = 1.0
-# Seed for the random number generator used for calculating normal modes extent
 STARTING_NM_SEED = 324324
+"""Seed for the random number generator used for calculating normal modes extent"""
 # When interpolating, which
 DEFAULT_NMODES_STEP = 0.5
 DEFAULT_REC_NM_FILE = "lightdock_rec.nm"
 DEFAULT_LIG_NM_FILE = "lightdock_lig.nm"
 
-"""Scoring function constants"""
-# LightDock default scoring function if none is specified
+# Scoring function constants
 DEFAULT_SCORING_FUNCTION = "fastdfire"
-# Threshold for an atomic-pair to be considered a contact (in Angstroms)
+"""LightDock default scoring function if none is specified"""
 DEFAULT_ATOMIC_CONTACT = 3.9
-# Threshold for an atomic-pair to be considered a contact in restraints definition (in Angstroms)
+"""Threshold for an atomic-pair to be considered a contact (in Angstroms)"""
 DEFAULT_CONTACT_RESTRAINTS_CUTOFF = 3.9
+"""Threshold for an atomic-pair to be considered a contact in restraints definition (in Angstroms)"""
 
-"""Default file extensions"""
+# Default file extensions
 DEFAULT_REFERENCE_POINTS_EXTENSION = ".vol"
 DEFAULT_LIST_EXTENSION = ".list"
 DEFAULT_RMSD_EXTENSION = ".rmsd"
 NUMPY_FILE_SAVE_EXTENSION = ".npy"
 DEFAULT_REPRESENTATIVES_EXTENSION = ".repr"
 DEFAULT_ELLIPSOID_DATA_EXTENSION = ".xyz"
 
-"""Default file names and folders"""
-# Folder which contains the initial_positions files for each swarm
+# Default file names and folders
 DEFAULT_POSITIONS_FOLDER = "init"
-# Simulation default output file
+"""Folder which contains the initial_positions files for each swarm"""
 GSO_OUTPUT_FILE = "gso_%s.out"
-# Folder where GSO execution for a given swarm will be stored
+"""Simulation default output file"""
 DEFAULT_SWARM_FOLDER = "swarm_"
-# Stores simulation step information
+"""Folder where GSO execution for a given swarm will be stored"""
 DEFAULT_SETUP_FILE = "setup.json"
+"""Stores simulation step information"""
 DEFAULT_PDB_STARTING_PREFIX = "starting_positions"
 DEFAULT_BILD_STARTING_PREFIX = "starting_poses"
 DEFAULT_STARTING_PREFIX = "initial_positions"
-# A special PDB file containing all swarm centers over the receptor surface
-# centered at origin of coordinates (use together with LightDock receptor parsed PDB)
 SWARM_CENTERS_FILE = "swarm_centers.pdb"
+"""A special PDB file containing all swarm centers over the receptor surface centered at origin of coordinates (use together with LightDock receptor parsed PDB)"""
 
 RANKING_FILE = "solutions.list"
 RANKING_BY_RMSD_FILE = "rank_by_rmsd.list"
@@ -82,20 +82,20 @@
 LIGHTDOCK_PDB_FILE = "lightdock_%s.pdb"
 CLUSTER_DEFAULT_NAME = "cluster"
 CLUSTER_REPRESENTATIVES_FILE = CLUSTER_DEFAULT_NAME + DEFAULT_REPRESENTATIVES_EXTENSION
-# Each independent simulation generates a new file:
 DEFAULT_LIGHTDOCK_INFO = "lightdock.info"
+"""Each independent simulation generates a new file"""
 DEFAULT_MASK_FILE = "lightdock_%s_mask" + NUMPY_FILE_SAVE_EXTENSION
 
-"""Swarm calculations"""
-# Total SASA will be divided by this number
+# Swarm calculations
 DEFAULT_SURFACE_DENSITY = 50.0
-# Swarm radius for the boundary of possible translations of initial poses
+"""Total SASA will be divided by this number"""
 DEFAULT_SWARM_RADIUS = 10.0
-# If this value is 0.0, swarm distance is estimated using the ligand max diameter
+"""Swarm radius for the boundary of possible translations of initial poses"""
 DEFAULT_SWARM_DISTANCE = 0.0
-# Number of swarms to keep when applying restraints
+"""If this value is 0.0, swarm distance is estimated using the ligand max diameter"""
 DEFAULT_SWARMS_PER_RESTRAINT = 20
-# Number of sampling points per centroid in automatic swarm calculation
+"""Number of swarms to keep when applying restraints"""
 DEFAULT_SPHERES_PER_CENTROID = 100
-# Cutoff for filtering swarms too close to the surface
+"""Number of sampling points per centroid in automatic swarm calculation"""
 SWARM_DISTANCE_TO_SURFACE_CUTOFF = 3.0
+"""Cutoff for filtering swarms too close to the surface"""

lightdock/gso/boundaries.py

@@ -41,5 +41,5 @@ def get_boundary_of_dimension(self, dimension_index):
         """Gets the Boundary of the dimension with dimension_index"""
         return self.boundaries[dimension_index]
 
-    def __repr__(self):
-        return " ".join([str(b) for b in self.boundaries])
+    def __repr__(self) -> str:
+        return " ".join(str(b) for b in self.boundaries)

lightdock/gso/coordinates.py

@@ -101,10 +101,8 @@ def move(self, other, step=1.0):
     def __repr__(self):
         """Coordinate representation"""
         # Path for equivalent representation from Python 2.7
-        coord = ["{:.12g}".format(f) for f in self._values]
-        return "(%s)" % ", ".join(
-            ["{}.0".format(f) if "." not in f else f for f in coord]
-        )
+        coord = (f"{f:.12g}" for f in self._values)
+        return "(%s)" % ", ".join(f"{f}.0" if "." not in f else f for f in coord)
 
     def __len__(self):
         return self.dimension

lightdock/gso/glowworm.py

@@ -26,7 +26,7 @@ def __init__(self, landscape_positions, gso_parameters):
 
     def search_neighbors(self, glowworms):
         """Searches in a list of glowworms for neighbors of this glowworm"""
-        squared_vision_range = self.vision_range * self.vision_range
+        squared_vision_range = self.vision_range ** 2
         self.neighbors = [
             glowworm
             for glowworm in glowworms
@@ -51,10 +51,8 @@ def compute_luciferin(self):
         """Updates luciferin of the current glowworm and returns its value"""
         if self.moved or self.step == 0:
             self.scoring = sum(
-                [
-                    landscape_position.evaluate_objective_function()
-                    for landscape_position in self.landscape_positions
-                ]
+                landscape_position.evaluate_objective_function()
+                for landscape_position in self.landscape_positions
             )
         self.luciferin = (1.0 - self.rho) * self.luciferin + self.gamma * self.scoring
         self.step += 1
@@ -74,16 +72,12 @@ def distance2(self, other, scoring_id=0):
 
     def compute_probability_moving_toward_neighbor(self):
         """Computes the probability of this glowworm to move towards any of his neighbors"""
-        self.probabilities = []
-
-        total_sum = 0.0
-        for neighbor in self.neighbors:
-            difference = neighbor.luciferin - self.luciferin
-            self.probabilities.append(difference)
-            total_sum += difference
 
-        for i in range(len(self.neighbors)):
-            self.probabilities[i] /= total_sum
+        differences = [
+            neighbor.luciferin - self.luciferin for neighbor in self.neighbors
+        ]
+        total_sum = sum(differences)
+        self.probabilities = [difference / total_sum for difference in differences]
 
     def select_random_neighbor(self, random_number):
         """Selects a neighbor in the neighbors list using accumulated probabilities of
@@ -133,10 +127,8 @@ def update_vision_range(self):
     def minimize(self):
         """Minimizes the glowworm's landscape position and updates its scoring"""
         self.scoring = sum(
-            [
-                landscape_position.minimize()
-                for landscape_position in self.landscape_positions
-            ]
+            landscape_position.minimize()
+            for landscape_position in self.landscape_positions
         )
 
     def __repr__(self):

lightdock/gso/searchspace/cython/j1.pyi

@@ -0,0 +1,6 @@
+"""J1: peaks function"""
+
+
+def j1(x: float, y: float) -> float:
+    """J1: peaks function"""
+    ...

lightdock/gso/searchspace/cython/j2.pyi

@@ -0,0 +1,6 @@
+"""J2: Rastrigin's function"""
+
+
+def j2(x: float, y: float) -> float:
+    """J2: Rastrigin's function"""
+    ...

lightdock/gso/searchspace/cython/j3.pyi

@@ -0,0 +1,6 @@
+"""J3: circles function"""
+
+
+def j3(x: float, y: float) -> float:
+    """J3: circles function"""
+    ...

lightdock/gso/searchspace/cython/j4.pyi

@@ -0,0 +1,6 @@
+"""J4: staircase function"""
+
+
+def j4(x: float, y: float) -> float:
+    """J4: staircase function"""
+    ...

lightdock/gso/searchspace/cython/j5.pyi

@@ -0,0 +1,6 @@
+"""J5: plateaus function"""
+
+
+def j5(x: float, y: float) -> float:
+    """J5: plateaus function"""
+    ...

lightdock/gso/swarm.py

@@ -1,6 +1,7 @@
 """The set of swarms of glowworm agents used in the algorithm"""
 
 from operator import attrgetter
+from pathlib import Path
 from lightdock.gso.glowworm import Glowworm
 
 
@@ -62,9 +63,9 @@ def get_size(self):
     def save(self, step, destination_path, file_name=""):
         """Saves actual population status to a file"""
         if file_name:
-            dest_file_name = "%s/%s" % (destination_path, file_name)
+            dest_file_name = Path(destination_path) / file_name
         else:
-            dest_file_name = "%s/gso_%d.out" % (destination_path, step)
+            dest_file_name = Path(destination_path) / f"gso_{step:d}.out"
 
         dest_file = open(dest_file_name, "w")
         dest_file.write(str(self))

lightdock/mathutil/cython/cutil.pyi

@@ -0,0 +1,44 @@
+from typing import Iterable
+
+
+def sum_of_squares(values: Iterable[float]) -> float:
+    """
+    Calculates the sum of squares of each value in values
+    """
+    ...
+
+
+def norm(values: Iterable[float]) -> float:
+    """
+    Calculates the norm of the given values
+    """
+    ...
+
+
+def float_equals(a: float, b: float, precision: float = 1e-7) -> bool:
+    """
+    Compares two floats for equality given precision
+    """
+    ...
+
+
+def sum_of_square_difference(v1: Iterable[float], v2: Iterable[float]) -> float:
+    """
+    Calculates the sum of the square differences of the components of 
+    v1 and v2 vectors.
+    """
+    ...
+
+
+def distance(x1: float, y1: float, z1: float, x2: float, y2: float, z2: float) -> float:
+    """
+    Calculates the distance between point 1 and point 2.
+    """
+    ...
+
+
+def distance2(x1: float, y1: float, z1: float, x2: float, y2: float, z2: float) -> float:
+    """
+    Calculates the distance^2 between point 1 and point 2.
+    """
+    ...